OpenBot
Egocentric datasetClosedReadiness 70/100Provisional

EgoMM

A tri-modal egocentric dataset built from EgoLife and Ego-Exo4D sources, packaged into fixed-duration clips with optional narrations.

Scale
463 hours
Formats
MP4 · MP3
License
Apache-2.0
Published
2026-05-10

Decision summary

Best for

Wearable-assistant evaluation

Main blocker

A practical bridge between video-only egocentric data and robot-ready sensor streams.

Next check

Read the dataset manifest and feature schema.

Release history

Source-backed release timing for this canonical dataset record.

Important releases
  1. Dataset series published

    Release timing is recorded from the official source creation date.

    Release evidence

Selection readiness

6 evidence dimensions for deciding whether this dataset is ready to inspect, compare, or adopt. This is not a model benchmark.

Catalog evidence · not task performance

How scores work

70/100

Provisional

2/6 dimensions scored · 35% confidence

Access and governance75conf. 85
Schema and signal coverageNot scoredconf. 15
Policy training readinessNot scoredconf. 15
World-model readinessNot scoredconf. 15
Failure and recovery readinessNot scoredconf. 15
Download and processing readiness65conf. 65
Read the evidence behind all 6 dimensions

Access and governance

Access and license are declared by the source.

usefulfit 75 · confidence 85

Schema and signal coverage

No machine-readable schema has been verified yet.

unknownnot scored · confidence 15

Policy training readiness

Observation/action alignment has not been established.

unknownnot scored · confidence 15

World-model readiness

World-model observation, geometry, or temporal semantics are not verified.

unknownnot scored · confidence 15

Failure and recovery readiness

No verified failure/recovery annotation evidence is available yet.

unknownnot scored · confidence 15

Download and processing readiness

Scale is declared; transfer and processing estimates are not measured.

usefulfit 65 · confidence 65
Review unresolved evidence and next checks

Signal gaps

  • Action / hand pose / robot state. Not enough evidence is available to classify this signal.
  • Gaze / attention. Not enough evidence is available to classify this signal.

Next checks

  • Read the dataset manifest and feature schema.
  • Run a bounded sample audit before assigning Strong readiness.
Engineering checks (OBRS) behind this record
Engineering checksBronze

Needs Audit

4/12checks passed

OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.

Standardization & Loaders2 / 25 pt
Physical & Action Quality2 / 25 pt
Semantic & Annotation20 / 20 pt
Real-World Validation0 / 15 pt
License & Compliance10 / 15 pt
Missing evidence and readiness gaps
  • A passing real-hardware test report is required.
  • A passing ingestion/pipeline test report is required.
  • A passing privacy and provenance review is required.

Dataset facts

Source
Hugging Face · ldkong/EgoMM
Evidence
official claim
Formats
MP4 · MP3 · NPZ · JSON
clips
55.5K
hours
463
narrated
22.1K

Loop signals

5/7 present or partial

Action / hand pose / robot state

No decision-grade evidence captured yet.

unknown
Gaze / attention

No decision-grade evidence captured yet.

unknown
View 5 more signal categories
Observation / ego video

video · A practical bridge between video-only egocentric data and robot-ready sensor streams.

present
Language intent / task phase

narration · A tri-modal egocentric dataset built from EgoLife and Ego-Exo4D sources, packaged into fixed-duration clips with optional narrations.

present
Feedback / correction / failure

Wearable-assistant evaluation

present
Sim-real pairing

Long-sequence reconstruction from clips

partial
License / format / access

Closed · Apache-2.0 · MP4 · MP3

present
Evidence details and provenance

Official signal claims

VideoAudioIMUIMUNarration

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

Pending. Metadata does not prove sample coverage, alignment, or file integrity.

curated source metadata

Integration notes

  • A practical bridge between video-only egocentric data and robot-ready sensor streams.
  • Good for testing OpenBot Data's multimodal schema adapters.